A microphone is a transducer that converts patterns of air pressure (i.e., an acoustic signal) into an electrical signal. In a typical dynamic microphone, a microphone diaphragm moves a coil relative to a magnetic field in order to cause current to flow within the coil. In a typical condenser microphone, a microphone diaphragm (e.g., a charged metallic plate, an electret, etc.) moves relative to a rigid backplate in order to cause current to flow from a power supply attempting to maintain a constant potential difference between the microphone diaphragm and the rigid backplate.
Wind noise can interfere with a microphone""s ability to sense an acoustic signal. For example, when a person speaks into a microphone, wind noise can mask out the person""s voice thus obscuring the person""s voice from a device attached to the microphone (e.g., an amplifier, a recorder, a transmitter, a speaker, etc.). Wind noise can also mask out vital acoustic information reducing the performance of automated systems such as automatic object/target recognition devices, direction finding systems, etc.
Some microphone assemblies include windscreens that cover microphones in order to reduce wind noise sensed by the microphones. One conventional windscreen, which is typically seen on top of a microphone held by a television reporter, is made of foam and has a spherical shape (e.g., a foam ball which is approximately 10 centimeters in diameter covering the microphone). Such windscreens have been used for many years and can be effective in suppressing wind noise (e.g., an annoying rumbling sound) that could otherwise obscure particular sounds of interest (e.g., the television reporter""s voice).
Some scientific experiments have attempted to electronically remove wind noise from sound and wind noise at a target location (e.g., to obtain an acoustic signature from a passing truck). In general, these experiments used a microphone for sensing sound and wind pressure, a set of hot-wire anemometers disposed around the microphone (e.g., a few millimeters from the microphone) for sensing wind velocity, and computerized equipment for storing and processing the sound and wind pressure sensed by the microphone and the wind velocity sensed by the set of hot-wire anemometers. A typical hot-wire anemometer is a fragile device that senses wind velocity by heating a short piece of wire (e.g., a 1.5 mm length of tungsten or platinum), and measuring the heat lost due to wind blowing past the wire (the heat or energy loss being directly related to the wind velocity).
One of the above-mentioned experiments occurred as follows. A first analog-to-digital (A/D) converter converted a signal from the microphone into a digitized sound and wind pressure signal which was stored in the memory of a computer. Simultaneously, a second A/D converter converted a signal from the set of hot-wire anemometers into a digitized heat-loss signal which was also stored in the memory. Next, a digital signal processor processed the sound and wind pressure signal and the heat-loss signal. In particular, an algorithm was applied to the heat-loss signal to generate wind pressure data, and the wind pressure data was subtracted from the sound and wind signal. Although the experiment provided mixed results, in theory the end result should have been a sound signal from the target location with wind noise removed.
An experiment along the lines mentioned above is described in an article entitled xe2x80x9cElectronic Removal of Outdoor Microphone Wind Noise,xe2x80x9d by Shust et al., Acoustical Society of America 136th Meeting Lay Language Papers, October, 1998, the teachings of which are hereby incorporated by reference in their entirety. Another experiment along similar lines is described in an article entitled xe2x80x9cLow Flow-Noise Microphone for Active Noise Control Applications,xe2x80x9d by McGuinn et al., AIAA Journal, Vol. 35, No. 1, January, 1997, the teachings of which are hereby incorporated by reference in their entirety. Such experiments provided some encouraging test results, but only when the wind flow was substantially normal incident to the microphone diaphragm. A related experiment and wind signal algorithms (e.g., fluid dynamic equations) are described in a dissertation entitled xe2x80x9cActive Removal of Wind Noise from Outdoor Microphones using Local Velocity Measurements,xe2x80x9d by Shust, Ph.D. Dissertation in Electrical Engineering, Michigan Technological University, Mar. 6, 1998, the teachings of which are hereby incorporated by reference in their entirety.
Unfortunately, there are deficiencies to conventional approaches to reducing wind noise sensed by a microphone. For example, the above-described conventional windscreens tend to be bulky thus hindering certain microphone applications (e.g., applications in hearing aids, hands-free telephone equipment, covert surveillance equipment, etc.). Additionally, the bulkiness of such windscreens hinders the current trend of microphone and acoustic system miniaturization (e.g., palm-sized camcorders, pocket-sized cellular telephones, etc.). Furthermore, windscreens cannot be miniaturized if their effectiveness in wind noise removal is to be maintained.
Additionally, in connection with the above-described conventional approach to electronically removing wind noise from a sound and wind pressure signal sensed by a microphone surrounded by a set of hot-wire anemometers, the approach provided mixed results and has not been shown to remove wind noise as effectively as windscreens. Such mixed results can be attributed to a number of factors. For example, the set of hot-wire anemometers did not sense wind noise from the same location as the microphone. Rather, the set of hot-wire anemometers sensed wind noise adjacent the microphone (i.e., a few millimeters away from the microphone) and such wind noise could have been significantly different than the wind noise at the microphone location. Also, as the wind passed the microphone toward the set of anemometers, the air flow around the microphone could have distorted the wind velocity at the anemometers thus introducing inaccuracies into the system. Furthermore, the approach worked well only when the wind was substantially normal incident to the microphone diaphragm.
Moreover, there are implementation deficiencies with the above-described conventional approaches to electronically removing wind noise. For example, some of the approaches required extensive computer equipment (e.g., multiple A/D converters, memory for storing signal information, the application of digital signal processing techniques to both a sound and wind pressure signal and a wind velocity signal, etc.). Furthermore, those approaches subtracted wind pressure data from a sound and wind signal after the signal information was digitized and stored in memory thus requiring computer memory and providing latency. Such post-processing approaches are unsuitable for certain applications such as in acoustic systems requiring active (i.e., real-time) wind noise removal, e.g., live broadcasts, cellular phones, military/defense ground sensors, hearing aids, etc.
In contrast to the above-described conventional wind noise reduction approaches, embodiments of the invention are directed to techniques for obtaining an acoustical signal using microelectromechanical systems (MEMS) technology. For example, sensing elements such as a microphone and a hot-wire anemometer can be essentially collocated (e.g., can reside at a location with a minute finite separation, or can be in contact with each other) in a MEMS device. Accordingly, wind velocity and sound and wind pressure can be measured at essentially the same location. As a result, an accurate wind pressure signal can be generated based on the wind velocity and then subtracted from the sound and wind pressure signal thus providing accurate sound with wind noise removed.
One arrangement of the invention is directed to an acoustic system having an acoustic sensor and a processing circuit. The acoustic sensor includes (i) a base, (ii) a microphone having a microphone diaphragm that is supported by the base, and (iii) a hot-wire anemometer having a set of hot-wire extending members that is supported by the base. The set of hot-wire extending members defines a plane which is substantially parallel to the microphone diaphragm. The processing circuit receives a sound and wind pressure signal from the microphone and a wind velocity signal from the hot-wire anemometer, and provides an output signal based on the sound and wind pressure signal from the microphone and the wind velocity signal from the hot-wire anemometer (e.g., accurate sound with wind noise removed). Since the hot-wire extending members define a plane which is substantially parallel to the microphone diaphragm, the hot-wire extending members and the microphone diaphragm can be positioned extremely close to each other (e.g., separated by a minute finite distance), or even in contact with each other, for accurate wind velocity and sound and wind pressure sensing at the same location.
In one arrangement, a first layer of conductive material defines the microphone diaphragm (e.g., polycrystalline silicon, silicide, etc.), and a second layer of conductive material defines the set of hot-wire extending members (e.g., tungsten). In this arrangement, the base includes a substrate (e.g., silicon) that supports both the first layer of conductive material and the second layer of conductive material. Accordingly, the acoustic sensor can be implemented as a MEMS device. Since such a MEMS acoustic sensor is capable of providing sound with wind noise removed, the MEMS acoustic sensor can be conveniently referred to as a MEMS Electronic Windscreen Microphone (MEWM).
In one arrangement, the microphone of the acoustic sensor further includes a rigid member (e.g., a backplate) that is substantially parallel to the microphone diaphragm to form a condenser microphone cavity. In this arrangement, a third layer of conductive material defines the rigid member of the microphone. The substrate supports the third layer of conductive material. Preferably, the microphone diaphragm extends in a contiguous manner to the base to form a seal between the set of hot-wire extending members and the condenser microphone cavity. Accordingly, the microphone diaphragm will prevent contaminants (e.g., dust, moisture, dirt, debris, etc.) from traveling in a direction from the set of hot-wire extending members toward and into the condenser microphone cavity where it could otherwise cause the microphone to operate improperly.
In one arrangement, the set of hot-wire extending members includes tungsten bridges that are substantially parallel to each other within the plane defined by the set of hot-wire extending members. Accordingly, the tungsten bridges can be heated and the heat loss due to wind passing by the tungsten bridges can be measured (e.g., via analog circuitry) in order to obtain heat loss values which can be converted into wind velocity signal.
In one arrangement, the acoustic sensor further includes a layer of protective material (e.g., silicon nitride) supported by the substrate. The layer of protective material preferably defines a mesh such that sound waves are capable of passing from an external location to the set of hot-wire extending members and to the microphone diaphragm through the layer of protective material. Accordingly, the mesh can allow sound and wind to pass from the external location to the anemometer and to the microphone, but also reduces the likelihood of contaminants reaching the anemometer and the microphone.
In one arrangement, the first layer of conductive material defines multiple microphone diaphragms including the microphone diaphragm. Preferably, the multiple microphone diaphragms are configured into a two-dimensional Nxc3x97M array of microphone diaphragms (N and M being positive integers). Additionally, a second layer of conductive material defines multiple sets of hot-wire extending members including the set of hot-wire extending members. Preferably, the multiple sets of hot-wire extending members are configured into a two-dimensional Nxc3x97M array of sets of hot-wire extending members that corresponds to the two-dimensional Nxc3x97M array of microphone diaphragms. Accordingly, the acoustic sensor can have multiple sensing elements (a microphone and anemometer pair) for robustness, e.g., for fault tolerance, an improved signal to noise ratio (i.e., to alleviate random noise at any particular sensing element), etc.
In one arrangement, the two-dimensional Nxc3x97M array of microphone diaphragms includes a first row of microphone diaphragms configured to respond to sound waves within a first frequency range (e.g., 0-10 Khz), and a second row of microphone diaphragms configured to respond to sound waves within a second frequency range that is different than the first frequency range (e.g., 10-20 Khz). Other rows can respond to other frequency ranges as well. Accordingly, the acoustic sensor can be specifically tailored to sense particular types of sound (e.g., voice, automobile signatures, etc.).
In one arrangement, the processing circuit includes a conversion stage that converts the wind velocity signal from the hot-wire anemometer into an analog wind pressure signal having a wind pressure component, and an output stage that subtracts the wind pressure component of the analog wind pressure signal from the sound and wind pressure signal from the microphone to provide the output signal. This arrangement can operate in real-time in order to provide, as the output signal, a real-time sound signal with wind noise removed. Accordingly, this arrangement is suitable for real-time applications requiring active wind noise cancellation such as live broadcasts, cellular phones, military/defense ground sensors, hearing aids, etc.
In one arrangement, the conversion and output stages are analog circuits which reside in an application specific integrated circuit (ASIC). Such packaging enables the entire system to reside in a miniature space (e.g., a MEMS device for the acoustic sensor and an ASIC device for the processing circuit).
In one arrangement, the processing circuit includes a correlation stage that digitizes the wind velocity signal, correlates the digitized wind velocity signal with a series of wind pressure values from a lookup table, and provides the series of wind pressure values in the form of a correlation signal. Here, the processing circuit further includes an output stage that (i) receives the correlation signal from the correlation stage, (ii) receives the sound and wind signal from the microphone, and (iii) subtracts the series of wind pressure values from the sound and wind pressure signal to provide the output signal. This arrangement enables an algorithm to be applied to the wind velocity signal. In this arrangement, the system does not need the conversion stage, or the conversion stage can be bypassed.
The features of the invention, as described above, may be employed in acoustic systems, devices and methods and other electronic equipment such as those of Textron Systems Corporation of Wilmington, Mass.